A simple mechanism for capturing and replaying wireless channels

Judd, Glenn; Steenkiste, Peter

doi:10.1145/1080148.1080161

Cited by 16 publications

(5 citation statements)

References 5 publications

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“…Then after a few minutes following the start of the experiment the power drops started to occur every 30 seconds. Similar power drops were also observed by Glenn Judd and Peter Steenkiste [15], however they suggested that these were "bogus RSSI values" reported by the receivers. However, we have observed these anomalous power drops are observed simultaneously on two or three independent receivers and thus cannot be explained as bogus values.…”

Section: Anomalous Power Control Observedsupporting

confidence: 78%

Practical issues of power control in IEEE 802.11 wireless devices

Kowalik

Bykowski

Keegan

et al. 2008

2008 International Conference on Telecommunications

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Abstract-Power control techniques for IEEE 802.11 wireless networks have already gained much attention. Such techniques are particularly attractive because they can improve various aspects of wireless network operation such as interference mitigation, spatial reuse in dense wireless deployments, topology control, and link quality enhancement. However, until recently implementing such advanced power control using off-the-shelf wireless devices was not considered possible. For example, Abdesslem et al.[1] stated that "many novel power control solutions cannot be efficiently implemented over existing IEEE 802.11 cards". However, in this paper we demonstrate that power control is now feasible and can be implemented in current IEEE 802.11 cards with per-packet granularity and low power switching latency.

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Section: Anomalous Power Control Observedsupporting

confidence: 78%

Practical issues of power control in IEEE 802.11 wireless devices

Kowalik

Bykowski

Keegan

et al. 2008

2008 International Conference on Telecommunications

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“…So new test system need to send real data. Reference [10] proposed a mechanism to play back real data for improving simulation accuracy. But this method must capture the overall data flow from every scenario that people want to simulate.…”

Section: A Related Workmentioning

confidence: 99%

A Replay Approach for Remote Testing User Experience of Mobile Bursty Data Application

et al. 2013

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â??The Bursty data applications become popular in mobile networks, and the quality of end user experience of these applications is vital for mobile telecom operators. Mobile telecom operators and equipment providers begin to design new scheduling strategies aiming at improving quality of user experience. These scheduling strategies can identify particular applications and assign corresponding scheme to them. But traditional test approaches only consider the common performance indicators, so they cannot evaluate the new scheduling strategies. This paper proposes an approach of replaying user behaviors to evaluate the communication system. The approach uses user behavior model to build test scenarios, and evaluate the performance of each application via corresponding particular indicators. Finally, a remote test system is built, and the experiment on this system proves the effectiveness of this approach

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“…Trace-driven emulation (see, e.g., [6], [7]) of the wireless channel typically entails recording representative traces from a physical deployment, training a model based on the traces, and then using the model to generate synthetic traces to drive emulation. Com- Figure 1: TCP throughput depends on run/gap sizes, rather than the mean packet loss rate.…”

Section: Related Workmentioning

confidence: 99%

A location-dependent runs-and-gaps model for predicting TCP performance over a UAV wireless channel

Kung

Lin

et al. 2010

2010 - Milcom 2010 Military Communications Conference

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In this paper, we use a finite-state model to predict the performance of the Transmission Control Protocol (TCP) over a varying wireless channel between an unmanned aerial vehicle (UAV) and ground nodes. As a UAV traverses its flight path, the wireless channel may experience periods of significant packet loss, successful packet delivery, and intermittent reception. By capturing packet run-length and gap-length statistics at various locations on the flight path, this locationdependent model can predict TCP throughput in spite of dynamically changing channel characteristics. We train the model by using packet traces from flight tests in the field and validate it by comparing TCP throughput distributions for model-generated traces against those for actual traces randomly sampled from field data. Our modeling methodology is general and can be applied to any UAV flight path.

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A simple mechanism for capturing and replaying wireless channels

Cited by 16 publications

References 5 publications

Practical issues of power control in IEEE 802.11 wireless devices

Practical issues of power control in IEEE 802.11 wireless devices

A Replay Approach for Remote Testing User Experience of Mobile Bursty Data Application

A location-dependent runs-and-gaps model for predicting TCP performance over a UAV wireless channel

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